Dose-Dependent Effects of Gonadotropin Releasing Hormone on Matrix Metalloproteinase (MMP)-2, and MMP-9 and Tissue Specific Inhibitor of Metalloproteinases-1 Messenger Ribonucleic Acid Levels in Human Decidual Stromal Cells<i>in Vitro</i>
Bibliographic record
Abstract
Matrix metalloproteinases (MMPs) and their endogenous inhibitors, tissue-specific inhibitor of matrix metalloproteinases (TIMPs), play key roles in the cyclic remodeling events that occur in the human endometrium in preparation for pregnancy. To date, the factors capable of regulating the expression of MMPs and TIMPs in the human decidua remain poorly characterized. The spatiotemporal expression of GnRH in the human endometrium during the menstrual cycle and early pregnancy suggests that this hormone may have a regulatory role in the development of this dynamic tissue. In view of these observations, we have examined the ability of GnRH to regulate MMP-2, MMP-9, and TIMP-1 mRNA levels in primary cultures of human decidual stromal cells using a quantitative competitive PCR strategy. GnRH was capable of increasing MMP-2 and MMP-9 mRNA levels in these primary cell cultures in a dose-dependent manner. The GnRH antagonist, antide, was capable of inhibiting the GnRH-mediated increase in the levels of the MMP-2 and MMP-9 mRNA transcripts present in these decidual stromal cells in a dose-dependent manner. In contrast, GnRH or antide did not have a significant effect on TIMP-1 mRNA level in these primary cell cultures at any of the concentrations used in these studies. Taken together, these observations suggest that GnRH plays an integral role in human implantation, by virtue of its ability to regulate the balance between MMP and TIMP expression in decidual cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".